Connectome-Based Prediction of Optimal Weight Loss Six Months After Bariatric Surgery.

ABSTRACT: Despite bariatric surgery being the most effective treatment for obesity, a proportion of subjects have suboptimal weight loss post-surgery. Therefore, it is necessary to understand the mechanisms behind the variance in weight loss and identify specific baseline biomarkers to predict optimal weight loss. Here, we employed functional magnetic resonance imaging (fMRI) with baseline whole-brain resting-state functional connectivity (RSFC) and a multivariate prediction framework integrating feature selection, feature transformation, and classification to prospectively identify obese patients that exhibited optimal weight loss at 6 months post-surgery. Siamese network, which is a multivariate machine learning method suitable for small sample analysis, and K-nearest neighbor (KNN) were cascaded

SUBMITTER: Zhang W 

PROVIDER: S-EPMC8248852 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature